|
|
Absolute deviation, 绝对离差7 R j+ K7 u9 o# h. W6 r
Absolute number, 绝对数- j# l2 y2 {2 W, ]3 q2 |# x X
Absolute residuals, 绝对残差
) h9 ~: _0 w x4 |# R+ I" `Acceleration array, 加速度立体阵
' {" A Q$ A5 IAcceleration in an arbitrary direction, 任意方向上的加速度
9 T6 M0 ^# m. _/ ~3 {( i# wAcceleration normal, 法向加速度3 x9 q/ l3 h' G R
Acceleration space dimension, 加速度空间的维数
& B3 C2 y4 S$ f0 q0 P kAcceleration tangential, 切向加速度* c3 m. L; E. i9 I8 S s. M
Acceleration vector, 加速度向量* D- e5 l2 r7 y" V. n: B1 ?% [
Acceptable hypothesis, 可接受假设
, i0 O9 Y+ q9 s! J0 o1 IAccumulation, 累积
& \5 U, a3 l5 q; _3 G2 BAccuracy, 准确度4 D' R# i8 Y8 X: g
Actual frequency, 实际频数
3 i4 C+ x+ S# a+ ]0 O/ OAdaptive estimator, 自适应估计量
( Y% T8 l, T' k' g3 Z: zAddition, 相加; _3 o$ z& b1 A, B. @) O, X0 o/ I
Addition theorem, 加法定理 t2 M6 ]% k/ c) K) ?
Additivity, 可加性
: ]2 y% a! G1 J4 z& f3 X) d: P' ?Adjusted rate, 调整率
, N9 w/ i; O2 j( H* I1 YAdjusted value, 校正值5 C' M1 P8 p/ `) s9 j6 t
Admissible error, 容许误差
. F9 | ?! x* I& M3 w% y+ HAggregation, 聚集性! t. M( c8 ~5 K% c
Alternative hypothesis, 备择假设3 a3 O$ D( @) Z7 Q4 f
Among groups, 组间
) o, P$ u# d6 F/ P$ cAmounts, 总量
0 O6 t4 X9 y/ X3 X5 E4 `Analysis of correlation, 相关分析
+ I3 W8 {3 G8 J9 l. I5 gAnalysis of covariance, 协方差分析
& Y; q _% M8 f2 dAnalysis of regression, 回归分析( `( T7 v3 a' R- w
Analysis of time series, 时间序列分析3 {6 h7 U4 Z5 `; e t t2 Z
Analysis of variance, 方差分析
% Q3 m9 O1 C+ x- P: y: k& }& S4 CAngular transformation, 角转换
% G. c5 y G# {$ R4 jANOVA （analysis of variance）, 方差分析3 X( l) [5 k9 `
ANOVA Models, 方差分析模型/ ~2 R. m& t- Q8 K" V
Arcing, 弧/弧旋
/ ]# m [+ I) h$ l% A; w4 m3 qArcsine transformation, 反正弦变换* D/ F$ `$ B" |7 K/ k
Area under the curve, 曲线面积: \: _: X$ d9 |+ [) z- n0 U
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
2 ^1 Z9 W |" y; PARIMA, 季节和非季节性单变量模型的极大似然估计
0 d' I2 I5 k6 i' G+ G1 E, D' NArithmetic grid paper, 算术格纸 y! E! w, w( G$ w2 |
Arithmetic mean, 算术平均数( o7 `/ E) w- M& _1 u
Arrhenius relation, 艾恩尼斯关系3 l& ?" t$ G3 J+ Q3 v
Assessing fit, 拟合的评估
# p) {( X- ?6 w' s4 S4 x% RAssociative laws, 结合律
4 r, f3 C; _/ J1 ` g: T- @& ?0 NAsymmetric distribution, 非对称分布
2 C. H# ^* [8 k' OAsymptotic bias, 渐近偏倚7 c* g1 s! n* |) a- W! n' }
Asymptotic efficiency, 渐近效率9 u( a" d4 F' B* c- I5 f/ V
Asymptotic variance, 渐近方差
) _+ F3 ~7 F9 x( _3 v' cAttributable risk, 归因危险度
- y8 A' c& e" V5 z3 M; Z5 KAttribute data, 属性资料; ^/ `" l2 c4 @. \0 w
Attribution, 属性* }7 n: g" _2 u' r0 t, m
Autocorrelation, 自相关# O+ } O2 [$ S3 Y9 @
Autocorrelation of residuals, 残差的自相关
% t7 N, y# k1 S; J3 J1 x5 vAverage, 平均数
5 |3 S5 ?1 k' R# w; EAverage confidence interval length, 平均置信区间长度
8 z+ ^) c: e+ ?9 ~Average growth rate, 平均增长率$ A. e5 Z8 `1 p% l+ G* f1 \
Bar chart, 条形图- Q# r2 m" T) t4 ^/ {0 \
Bar graph, 条形图9 `7 G6 c( p7 ]9 n+ ?0 l
Base period, 基期
8 o# x/ }8 E5 u0 `, ABayes' theorem , Bayes定理/ f4 D: F% T. Q1 B! O$ M
Bell-shaped curve, 钟形曲线2 \$ a8 ^' |4 w; B8 `
Bernoulli distribution, 伯努力分布
: q3 Q. s) e+ j- @) b% w; {9 U, B2 IBest-trim estimator, 最好切尾估计量# V2 Q! o% \* Y+ Y2 f# n2 q. b
Bias, 偏性) e5 @4 f/ _4 `" h
Binary logistic regression, 二元逻辑斯蒂回归% K; |* A# q }
Binomial distribution, 二项分布
N. ?4 i5 K$ j- H. aBisquare, 双平方
/ O4 I% f9 B" Q" F: q! e8 T fBivariate Correlate, 二变量相关) V* {4 k* d3 c, C
Bivariate normal distribution, 双变量正态分布
]. d4 a; o4 m4 G# W( R7 TBivariate normal population, 双变量正态总体% ^8 N: Y& H$ ?+ Q$ |
Biweight interval, 双权区间7 d# B$ C! r# Q- R
Biweight M-estimator, 双权M估计量
* w# d" k: |/ t0 EBlock, 区组/配伍组
9 m' I' D" K# D2 ]) h: x1 IBMDP(Biomedical computer programs), BMDP统计软件包
! b5 i: p" S+ rBoxplots, 箱线图/箱尾图
( p; j+ n3 w- [' o2 j" `2 iBreakdown bound, 崩溃界/崩溃点( p: X! V8 Z" G* E7 O
Canonical correlation, 典型相关1 B# P; k% t- k$ x
Caption, 纵标目
7 E! T' L. c' f* X7 v1 kCase-control study, 病例对照研究
8 r3 ~8 Y$ {- WCategorical variable, 分类变量
% Y$ z% Q/ n& f5 {Catenary, 悬链线8 n. ?3 r5 Y' D; v% [. C
Cauchy distribution, 柯西分布
$ _4 n8 i7 _$ M" lCause-and-effect relationship, 因果关系# a5 f- H- S3 {" H
Cell, 单元
: Q" i/ ^$ R$ Q0 `Censoring, 终检9 I' ~ `/ w9 o& E
Center of symmetry, 对称中心
2 q. L" v) D; v# N2 ?8 [Centering and scaling, 中心化和定标& I; u* L' t7 z$ G
Central tendency, 集中趋势
7 \7 A. [, B, Q2 C8 M! ACentral value, 中心值+ d9 T. z8 W2 F9 w' }
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测4 ~. T( s7 O$ p# T
Chance, 机遇* _ P% @6 c! k0 S& D1 [
Chance error, 随机误差. [2 X9 v- Z8 S8 W2 _5 f# M L! l
Chance variable, 随机变量
5 i6 @* {6 |$ E% A8 Z$ C$ l( B, cCharacteristic equation, 特征方程
8 O6 u' U3 l9 @7 Q7 ] XCharacteristic root, 特征根& y, v4 N5 L0 F7 D& O
Characteristic vector, 特征向量
9 V4 }. H2 f6 e6 ?Chebshev criterion of fit, 拟合的切比雪夫准则
8 Y3 t0 w. e+ D1 v) I4 [ q* KChernoff faces, 切尔诺夫脸谱图
8 d9 g& r" D% k/ S' u8 ~% @Chi-square test, 卡方检验/χ2检验
; O2 Z& O% F( }9 d* ?( s9 sCholeskey decomposition, 乔洛斯基分解
, B# W4 J$ ?& o, U2 E1 D1 g% ~Circle chart, 圆图
3 \& {' |) q- f5 FClass interval, 组距
+ _/ G: Q5 j+ EClass mid-value, 组中值2 M( _) v* r8 @( ]
Class upper limit, 组上限
2 q# |! `' P2 C* f5 d' U3 p9 Z% FClassified variable, 分类变量
! x" e5 n5 P; sCluster analysis, 聚类分析
) r& u& t+ s/ L0 bCluster sampling, 整群抽样0 i; ?7 R: }) [7 S, W4 y$ w1 Z$ I
Code, 代码8 ^+ \7 j# m, S* I/ G% c
Coded data, 编码数据, A' F3 r4 T6 w$ L$ X
Coding, 编码
2 Z0 u& }6 w, o8 W X$ RCoefficient of contingency, 列联系数
( G4 M- r( ?8 ICoefficient of determination, 决定系数
4 I. j/ ?) e' r \0 q: J. aCoefficient of multiple correlation, 多重相关系数
' U* E3 \3 n; D% \Coefficient of partial correlation, 偏相关系数
5 d* ~' l* G8 R9 ~( c: I* [Coefficient of production-moment correlation, 积差相关系数
! Z# J% H* k7 s3 X6 jCoefficient of rank correlation, 等级相关系数
: E2 v, Y3 C% c% O& b$ _$ RCoefficient of regression, 回归系数3 N3 D7 \ A7 S: Z! {" n- E
Coefficient of skewness, 偏度系数 K* G8 `1 O9 r" D+ C) D4 H/ d
Coefficient of variation, 变异系数$ w, _* S% v* K
Cohort study, 队列研究
) _& U! @, q8 b+ Q+ ZColumn, 列% |1 R! H( I7 Z# e
Column effect, 列效应+ E3 g; t% I) @, z x, Y( } O
Column factor, 列因素
G! K8 k; H/ K3 T3 eCombination pool, 合并, m- K! k% H& s# ]' ?( F; n/ P# ]$ L
Combinative table, 组合表
$ X- f5 t. V) @Common factor, 共性因子
1 f d) h" A" O- ZCommon regression coefficient, 公共回归系数
8 m: `5 h, a2 CCommon value, 共同值. b) W& O/ X! y6 w$ y# a
Common variance, 公共方差
1 C9 M) \, i; D4 ^3 [1 JCommon variation, 公共变异
' b5 q5 z1 \8 e! I$ KCommunality variance, 共性方差/ u. T: \3 r5 ^) c' y2 u, o
Comparability, 可比性
4 q# O- z7 Y. [; wComparison of bathes, 批比较
; L* r: j- H7 M9 j9 @# h) PComparison value, 比较值
' U4 n2 [0 S8 CCompartment model, 分部模型
( v& \, X' O, }2 L+ ~Compassion, 伸缩0 q& [# z7 w# ?" g! T3 {' d
Complement of an event, 补事件
, l* c$ \7 C [0 r. L& {Complete association, 完全正相关
+ L9 U/ D. Y( V% S5 w; _8 ^Complete dissociation, 完全不相关# \2 i$ d( q9 f7 u Q& m( E2 |3 F
Complete statistics, 完备统计量2 i g) F7 Z0 s
Completely randomized design, 完全随机化设计! s8 G& w7 i8 Z6 S# G$ y
Composite event, 联合事件% \) z! q$ u, m& s4 M7 H+ e) {
Composite events, 复合事件# X' q/ [* { M. w" g
Concavity, 凹性
" j5 c+ e& K' \Conditional expectation, 条件期望
$ X* l* d& L; J% G& i& c* w4 qConditional likelihood, 条件似然) y( K2 u x# b
Conditional probability, 条件概率
. i! H* d9 k; ^ s# u4 dConditionally linear, 依条件线性1 B/ {; k7 t, @2 H2 U
Confidence interval, 置信区间& l/ k2 o% P( ?, q
Confidence limit, 置信限
) `6 S$ ~ W* [ n5 b i+ i& |Confidence lower limit, 置信下限
( |* G4 q0 S! s uConfidence upper limit, 置信上限
$ w! A9 z( g- F. P# o. `3 PConfirmatory Factor Analysis , 验证性因子分析
; c( h. a/ h2 z8 T+ L0 TConfirmatory research, 证实性实验研究' t4 H% Y$ F8 F: e
Confounding factor, 混杂因素
/ q; B" j' S5 ]& H% `8 q7 yConjoint, 联合分析/ ?$ _7 S. m$ L) \7 H4 t) [9 i
Consistency, 相合性: g! K7 h4 \7 |' E* d
Consistency check, 一致性检验
, U7 N6 F6 _3 v9 @Consistent asymptotically normal estimate, 相合渐近正态估计' i& m7 X, ~$ V( Z
Consistent estimate, 相合估计; A$ M, K+ Q3 ]
Constrained nonlinear regression, 受约束非线性回归
9 j y/ r- R& ^# UConstraint, 约束; @- s2 |% A* x' K. X
Contaminated distribution, 污染分布
3 D$ f8 M: M' z F0 b- T7 I/ KContaminated Gausssian, 污染高斯分布
7 ]8 [0 x8 N! GContaminated normal distribution, 污染正态分布
3 v/ y5 X: ]! j+ o1 \. S: a' EContamination, 污染/ b V9 U% A# Q Q
Contamination model, 污染模型
]- m8 W% K8 t1 IContingency table, 列联表* j, T( U( w9 D* ]
Contour, 边界线1 ?4 s0 ~; L* m- o, a& a* j
Contribution rate, 贡献率
/ V& F4 k @, ~% a8 z: B, sControl, 对照
: G7 D- t6 s# Q& z! IControlled experiments, 对照实验 c4 y E- y0 _, v
Conventional depth, 常规深度
& ~& G; \% k' t$ j' s( b. LConvolution, 卷积2 W% W+ q/ @$ K G7 ^& {
Corrected factor, 校正因子
: L n, Z( o8 ?* {. k2 D8 `; d) sCorrected mean, 校正均值
0 B' w6 ?6 q% f6 C( ?4 QCorrection coefficient, 校正系数) U' D! B7 K1 q+ F- w0 A4 r6 X3 g7 c' g
Correctness, 正确性
" b$ E j9 B. y6 G1 LCorrelation coefficient, 相关系数4 Q: J: j9 A# u9 G" S: T4 e v
Correlation index, 相关指数
) t2 S9 Y {; s. dCorrespondence, 对应
& s$ p4 x9 M* ^) z! a" D0 Z) w QCounting, 计数# O3 S3 w; _. `
Counts, 计数/频数! m% s. i2 y( H- I! Q
Covariance, 协方差, u/ c0 |6 H/ R8 J& y' W6 c
Covariant, 共变 ' H: l* D& \( a9 a+ V
Cox Regression, Cox回归. E- G$ ^) [; m5 v! F [& c' j7 i" R
Criteria for fitting, 拟合准则
' m4 ~' f6 k% T) aCriteria of least squares, 最小二乘准则
# W1 b8 k! h) t' g$ JCritical ratio, 临界比- c4 t! S: o& o& A
Critical region, 拒绝域
3 L$ c. f! w( j+ eCritical value, 临界值
. r: a# [, i0 _0 N9 L, \' l* w8 E. w% dCross-over design, 交叉设计
$ l% X# ^% k2 YCross-section analysis, 横断面分析3 t* H5 U# e! e3 ]& i
Cross-section survey, 横断面调查
, T, ~6 j/ A1 E: [9 K. ^+ sCrosstabs , 交叉表 2 O( X6 S$ ?+ F7 H" G. p
Cross-tabulation table, 复合表
) Q6 [: O* i& p: A+ CCube root, 立方根! }' H: O# i* r* d% Q: J
Cumulative distribution function, 分布函数
/ u4 ~5 ], P. XCumulative probability, 累计概率
; }/ l2 m& f, ^, SCurvature, 曲率/弯曲2 ? `8 ?( @% P7 `+ j
Curvature, 曲率" x5 S# y/ H4 D& c
Curve fit , 曲线拟和
; @% w6 }6 N; _6 Z/ |3 v' L% [Curve fitting, 曲线拟合
4 R# K- }/ s) ^% ICurvilinear regression, 曲线回归
- i- L7 D# ^$ j* iCurvilinear relation, 曲线关系
5 G3 U7 H, E, i' b6 O5 h6 k+ JCut-and-try method, 尝试法
. z0 I( m: e5 w; u9 a# s0 _3 u U' sCycle, 周期
8 H3 j% T& H7 j( RCyclist, 周期性% D6 t8 {- F- C
D test, D检验* h0 U$ h$ g2 u" J6 m' b" a# v& m
Data acquisition, 资料收集
$ _! E: g7 l" U: } b, PData bank, 数据库
& y/ l; N% B/ O% r& z7 d( N4 ~Data capacity, 数据容量
: E( H) N: @' @, {- A% `! vData deficiencies, 数据缺乏
( k! p& c3 w% _3 ?0 J IData handling, 数据处理& I8 q; N, |7 s8 R: a
Data manipulation, 数据处理
% d5 i( T, M# |. C, d8 I- I7 wData processing, 数据处理" O. _" s5 g) {0 a; L
Data reduction, 数据缩减* p& i B* P( s* r3 D3 p
Data set, 数据集
# P' Y) }# B, o+ U7 ?- c5 TData sources, 数据来源
4 c( G8 W" Q0 V: E; v) X2 ?% u4 q; ^Data transformation, 数据变换
/ }- T) s$ ]. q2 V$ s7 ^) ?Data validity, 数据有效性# M+ Y1 C) c [% p- a0 M3 K
Data-in, 数据输入! s, o4 ?& d1 l f6 z7 X/ H% F2 i
Data-out, 数据输出
# y% }9 a: |8 T4 Q8 [0 H4 GDead time, 停滞期
5 s, T1 ~! a( I9 J7 m% P# GDegree of freedom, 自由度1 l( d2 P4 |/ j- C. h
Degree of precision, 精密度
/ ]" Z" |7 `) H; t3 G. N+ R" zDegree of reliability, 可靠性程度
' W% H; Z: Z6 A9 O. s2 B' kDegression, 递减
) F. c& l# o# _9 y0 T- z0 x4 pDensity function, 密度函数
' P9 A6 p( r3 X' t7 X, D* PDensity of data points, 数据点的密度
* l& V8 w, {5 N# ^( n& J# u6 eDependent variable, 应变量/依变量/因变量% c `# O' S+ K& k9 X/ p- [
Dependent variable, 因变量! Y. e( e: D6 L6 s
Depth, 深度
6 v8 v" B' W1 E4 z4 R. bDerivative matrix, 导数矩阵, t" @8 t4 R4 Z7 d' j0 c6 _
Derivative-free methods, 无导数方法& ]% Q( T r \' t6 U8 k" h+ V
Design, 设计
9 ^+ H I' w7 Z( d5 yDeterminacy, 确定性$ y9 v H4 b* |% u
Determinant, 行列式
+ A( k" r& Z1 h2 v: `Determinant, 决定因素$ g5 I" D) B! ~1 b: l q
Deviation, 离差
' |, C5 F3 b. G% R. I. R7 vDeviation from average, 离均差9 u0 V/ c4 `3 g q' _$ p
Diagnostic plot, 诊断图
" }% c) R! T$ Y% s4 A0 O. `5 _0 G* XDichotomous variable, 二分变量0 U7 N, Q3 R1 h
Differential equation, 微分方程
9 P% i" ?& F6 q6 C# DDirect standardization, 直接标准化法
6 L( U7 Q7 [6 M' G6 aDiscrete variable, 离散型变量, G4 F: R' d' t& E! u
DISCRIMINANT, 判断
# X( e5 J6 T7 _5 R9 HDiscriminant analysis, 判别分析
- Q- F6 b3 \; s3 I9 e2 X. t7 kDiscriminant coefficient, 判别系数& Y& P: I3 ?* v" W1 N
Discriminant function, 判别值- r8 D8 W" @" b0 x
Dispersion, 散布/分散度
( A, _! V) u5 c1 ADisproportional, 不成比例的
0 @5 t" C) k' D2 b% E$ xDisproportionate sub-class numbers, 不成比例次级组含量
- W( O" j# m, H* H$ U5 B' a$ k' cDistribution free, 分布无关性/免分布0 f; i) a0 Y4 e3 j1 S
Distribution shape, 分布形状
, |7 {7 G8 y7 r6 [# GDistribution-free method, 任意分布法$ T8 j* A/ k4 k
Distributive laws, 分配律1 X* @4 C5 ?) R5 g! c. a1 c
Disturbance, 随机扰动项
* n* g# F6 ` G% CDose response curve, 剂量反应曲线* s3 j8 C8 m K$ N6 a* H
Double blind method, 双盲法2 A$ ]+ F, A+ x; a/ g; ?
Double blind trial, 双盲试验/ ~8 r8 N" v1 ?3 v6 {5 ?2 W& j
Double exponential distribution, 双指数分布 I: Q$ C9 a$ p7 E
Double logarithmic, 双对数
! Q# M O5 m- G$ Z, d" ]Downward rank, 降秩! c9 v% l. t( ?( I7 t0 ?% s$ ?
Dual-space plot, 对偶空间图
7 w0 w' ?' ?1 _7 s7 r4 ?DUD, 无导数方法
" L' b# I5 I3 nDuncan's new multiple range method, 新复极差法/Duncan新法
* S* \, ]/ @+ x, T" [# `: {Effect, 实验效应 b4 ^- W- Q2 u! P- I# [5 i; P
Eigenvalue, 特征值
" q+ Y2 h3 B9 GEigenvector, 特征向量# p+ ~5 m. i: {3 V$ i
Ellipse, 椭圆% x) I( W5 M( `6 @" `
Empirical distribution, 经验分布* n4 b5 {1 \0 \8 d
Empirical probability, 经验概率单位
! U1 a& U8 j' q; x0 m% i7 l YEnumeration data, 计数资料- t! `- r# T7 o$ q
Equal sun-class number, 相等次级组含量
! C7 o; ~6 r: n1 Z }+ K" `Equally likely, 等可能
* p O" M }7 K; ~5 `) I- ^ rEquivariance, 同变性
* H7 C* e4 W6 _; fError, 误差/错误
- j2 r& l! Q8 kError of estimate, 估计误差2 ~/ [. W: S. u
Error type I, 第一类错误
1 z' @- G: [& T$ l, pError type II, 第二类错误
6 R+ ], ?. B3 F0 `( C7 S, yEstimand, 被估量2 I8 i+ |9 g) \3 h& K4 s- [
Estimated error mean squares, 估计误差均方' R0 K- [9 ~4 S- z3 Z( l( x; F# F* L
Estimated error sum of squares, 估计误差平方和2 c% M! \! ]( J7 U$ v
Euclidean distance, 欧式距离% I' [) l+ p( e( G& a/ G; R
Event, 事件2 ?+ h: E: i5 |2 u6 I' p; B. C+ h
Event, 事件/ z( S3 Q7 j) h2 b
Exceptional data point, 异常数据点 W. r: `( c, F9 h5 m9 v4 R" V3 ]
Expectation plane, 期望平面% c7 E* S% A& m. T- V) L
Expectation surface, 期望曲面
% x( ]; H! I8 Q$ M! T0 ~; d$ JExpected values, 期望值
2 M5 C$ i+ G& Q1 b& a* }Experiment, 实验
0 ]3 Y* e- [* x$ rExperimental sampling, 试验抽样$ v9 d. m; ]: T- g/ F
Experimental unit, 试验单位
% z% p: k' b5 t- _# Z) s+ gExplanatory variable, 说明变量
$ `& A1 N0 q" ~* Q: MExploratory data analysis, 探索性数据分析: \( j% Z; v0 X9 |& i6 C4 k3 o
Explore Summarize, 探索-摘要
5 t0 D# B) T' SExponential curve, 指数曲线
7 }# ~: s% M/ Z4 _3 ~Exponential growth, 指数式增长
- |# j1 l3 D* h' OEXSMOOTH, 指数平滑方法
9 Y. J0 l1 Q6 S" Y5 A' VExtended fit, 扩充拟合5 ^1 X( k4 D7 c$ |
Extra parameter, 附加参数
6 o8 C7 S9 L. NExtrapolation, 外推法
% X5 e# m. c( |- t/ D% }Extreme observation, 末端观测值) L# R* q. W3 {9 b K0 [
Extremes, 极端值/极值; ]3 k+ a7 _; z3 d5 w% p
F distribution, F分布& H: Z) l4 l1 m4 c! z
F test, F检验
3 A9 {0 g- T3 Z6 m7 EFactor, 因素/因子
; K$ D3 n4 g5 u+ _0 q7 E2 QFactor analysis, 因子分析1 s/ }+ i4 Q, S$ l( i
Factor Analysis, 因子分析; T3 e% r+ e. U8 F4 T
Factor score, 因子得分
! O3 Z9 ?" o5 Y! {Factorial, 阶乘
3 i6 C6 G) f" FFactorial design, 析因试验设计
6 l' B0 [( i7 j4 _, z& SFalse negative, 假阴性
4 q: |( b, a) Q3 m3 V, p8 {6 zFalse negative error, 假阴性错误
9 K2 t8 g' w* YFamily of distributions, 分布族( z( F0 D/ q& |! k# K; E Y% m
Family of estimators, 估计量族
" t# l& J4 n" Z9 K3 M0 VFanning, 扇面
' b( x" c% J& k3 N5 SFatality rate, 病死率& Y+ c$ ~4 x( Q8 J! r" B
Field investigation, 现场调查 W1 u3 q! \1 N. o7 F' H
Field survey, 现场调查' Z1 K: Y( U- d& X& ]
Finite population, 有限总体: y) k# h) }6 O. @+ ~8 Z
Finite-sample, 有限样本9 q! [' g3 w' ?1 K
First derivative, 一阶导数
. g+ q( z# [3 I5 A' i- FFirst principal component, 第一主成分
" h, n# {1 e# `. R, g9 ~ S2 WFirst quartile, 第一四分位数; S Q8 ?+ {* A( u, A h- k' u
Fisher information, 费雪信息量: W" f, i" ~; s9 x2 O" E. g
Fitted value, 拟合值8 C6 f: u- [/ J4 c, L5 q, \# c
Fitting a curve, 曲线拟合
4 }) `" | ?4 y( X O7 N$ {6 iFixed base, 定基 J; [( ^+ n. R6 W% w0 R# k
Fluctuation, 随机起伏
|" i F6 n7 H/ h. SForecast, 预测* z6 O# x! \. M( }* V9 Z8 i
Four fold table, 四格表
$ g& S3 P2 w/ r) v; H' H ^1 wFourth, 四分点
& k6 B: @; J) l8 HFraction blow, 左侧比率
$ k1 r3 p# g; F& N8 a& [Fractional error, 相对误差
, t. C% \* L* ^! s7 K' E7 t; ]Frequency, 频率( R7 t& w0 r, b8 p
Frequency polygon, 频数多边图
, w3 m2 X9 l4 B$ T/ Z- rFrontier point, 界限点
0 C( c$ y' C7 i `2 L- O6 GFunction relationship, 泛函关系
u) K9 |" I% e) FGamma distribution, 伽玛分布( A, K. n2 b5 q, E$ h
Gauss increment, 高斯增量, t3 T4 ]. O* j' k0 ~
Gaussian distribution, 高斯分布/正态分布
5 R& Q, r/ ^ m2 jGauss-Newton increment, 高斯-牛顿增量' Y0 A o* A V. `* X/ E
General census, 全面普查
8 x0 H- v. i K& i# DGENLOG (Generalized liner models), 广义线性模型
- T0 p1 Q. I8 E: LGeometric mean, 几何平均数
: W7 S* ^! v) H6 a9 \. r9 d! rGini's mean difference, 基尼均差
* E4 V1 q# Q4 a% _9 F, QGLM (General liner models), 一般线性模型
; J9 p5 m+ ^4 s/ P0 E6 L9 ^7 EGoodness of fit, 拟和优度/配合度
8 z- L& ^& a0 RGradient of determinant, 行列式的梯度
: \* w* l( N: xGraeco-Latin square, 希腊拉丁方
+ N! \2 p6 J5 I3 E9 X8 }Grand mean, 总均值4 }; ]' P3 i4 _# j! X5 a: u
Gross errors, 重大错误7 o5 ]# B. x, |" ^; G1 A# P
Gross-error sensitivity, 大错敏感度, U% ?$ _+ {4 Z* [% k3 j
Group averages, 分组平均2 N# }% z; Y5 L% h0 X# A
Grouped data, 分组资料# Z, P. j) X" g$ k
Guessed mean, 假定平均数
7 ]' j- k/ h, ?+ g4 q2 GHalf-life, 半衰期
3 ]7 p, }( U6 Q8 r' l1 `5 PHampel M-estimators, 汉佩尔M估计量: `4 P' v6 T$ {9 N- Y
Happenstance, 偶然事件
J! N/ _7 I4 N' ]& a4 {5 ~Harmonic mean, 调和均数
- L A; k, Y+ F: M4 V' c- h- h. aHazard function, 风险均数7 e% J" N; M1 i+ u
Hazard rate, 风险率6 S# v: P/ \- x7 d9 U
Heading, 标目
( n* P- z& c0 N. z, MHeavy-tailed distribution, 重尾分布
8 h" Z w6 m) w# dHessian array, 海森立体阵% r+ ]! Q- Q# m, Q( v
Heterogeneity, 不同质
$ ?% F2 O# C( w0 ?. T5 R+ HHeterogeneity of variance, 方差不齐 Q( `2 s" z! a5 z. ^! }+ K U( w
Hierarchical classification, 组内分组5 z* D! Z7 I R+ L
Hierarchical clustering method, 系统聚类法1 i, W0 Y( Y9 _/ \
High-leverage point, 高杠杆率点 W' P% U; S8 l8 b. d+ L0 \# T
HILOGLINEAR, 多维列联表的层次对数线性模型
; W5 [* ~' q+ THinge, 折叶点 W0 M4 S9 B/ e# a
Histogram, 直方图! I. ?1 }& V4 D% N
Historical cohort study, 历史性队列研究
/ b. [9 d8 o8 dHoles, 空洞: D; r: {0 t5 V1 c
HOMALS, 多重响应分析
8 T) E" o; }& F& k2 [/ P/ @2 }Homogeneity of variance, 方差齐性. }/ @% A g$ g& ?, k
Homogeneity test, 齐性检验
; N# N$ ~) d) G& Z% n, s1 q9 AHuber M-estimators, 休伯M估计量 t D6 }# x% N8 i
Hyperbola, 双曲线0 |' e' k; K1 H( g
Hypothesis testing, 假设检验2 N. `4 Z# s5 L1 k2 p
Hypothetical universe, 假设总体
9 K- J& T2 l' w/ M( w/ ]+ YImpossible event, 不可能事件# R9 I9 ?6 j! w# g
Independence, 独立性5 u2 c+ a7 A4 k! J3 m/ M
Independent variable, 自变量
; c1 A" ?6 ^3 S1 \: o( `3 `Index, 指标/指数# E- d; r- e% t5 f# H: `$ L% v
Indirect standardization, 间接标准化法
o3 `3 m8 [0 p0 YIndividual, 个体, t4 c' r/ D" r! K
Inference band, 推断带9 {" f! ^2 n: [" T$ `8 D( _" M
Infinite population, 无限总体$ y+ S$ O6 _4 S4 Z# @
Infinitely great, 无穷大
* Z; |; o/ h% t3 Q5 K% ~0 Y. ZInfinitely small, 无穷小
. K6 F- c. d- U% C/ _: LInfluence curve, 影响曲线: e. ~: s5 K# a: `
Information capacity, 信息容量
E1 _' {7 C/ E3 H# c% W8 @9 U, MInitial condition, 初始条件) d( K& I7 J4 B
Initial estimate, 初始估计值3 W* {3 L: H3 n) C
Initial level, 最初水平6 w& V$ p: c+ o( x
Interaction, 交互作用* X0 t; u X9 |0 g
Interaction terms, 交互作用项0 ^+ a; W+ {( ~2 P9 j" c
Intercept, 截距
; f, q" K" |1 P6 B; }- N2 \Interpolation, 内插法
9 G$ U0 s* @! D& i+ H' p3 tInterquartile range, 四分位距- I) ~3 ~: ^' p8 v8 W o; w
Interval estimation, 区间估计6 x9 @$ `) c4 G# Q: h0 K! c! x
Intervals of equal probability, 等概率区间8 X3 H8 ^2 Q8 o: A; q( Y
Intrinsic curvature, 固有曲率
' i6 w5 { `* v# _$ E DInvariance, 不变性
$ E# P/ m% D4 ^$ R0 w$ Z3 l! E" aInverse matrix, 逆矩阵9 ~' S* x" D' @+ _- O; z
Inverse probability, 逆概率& I6 n1 e, j$ m$ U# _9 U
Inverse sine transformation, 反正弦变换6 w) J j% i8 |1 u
Iteration, 迭代 $ h. z3 f5 ~+ n# x" d+ Q4 j4 c% {
Jacobian determinant, 雅可比行列式- N2 D8 M) N9 X
Joint distribution function, 分布函数+ @5 B* s- r0 N
Joint probability, 联合概率
$ x& s1 w- S1 s. T3 oJoint probability distribution, 联合概率分布. v& ~' o: g, c3 p9 S) s, g
K means method, 逐步聚类法: C) v" l# T' w; F; Z& m! |
Kaplan-Meier, 评估事件的时间长度 1 h% ^& {1 I7 [" U& C( x* p
Kaplan-Merier chart, Kaplan-Merier图
/ c1 P0 t! Y7 \6 lKendall's rank correlation, Kendall等级相关+ f8 r9 I- g- K# y0 }& d& r
Kinetic, 动力学" I3 J0 ]) {9 ~" i8 `' u
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
* R, O% A4 K$ [4 a" w' G7 P/ B8 ZKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
/ f0 f; q8 u0 h- JKurtosis, 峰度4 n% d8 ] i Z# E; }6 x& g
Lack of fit, 失拟
) R- U5 w- x+ ]1 P3 ]" w8 u+ PLadder of powers, 幂阶梯5 }% L. |0 B C( ]3 c) e( n
Lag, 滞后
8 N, G. l6 ^: I# O& U1 iLarge sample, 大样本" y5 a E- \' P! v$ z; Z L ^
Large sample test, 大样本检验
: o9 j7 J1 v+ j! s, w* QLatin square, 拉丁方( v4 t( q, {8 F. @$ p: p5 t3 A
Latin square design, 拉丁方设计
& ^1 ~3 Z4 @: \9 c6 c) fLeakage, 泄漏
8 n( r7 V7 O i3 }2 p. w2 SLeast favorable configuration, 最不利构形
, d7 ?, }# {. o9 j/ ^ y1 rLeast favorable distribution, 最不利分布
0 h, F R. O3 r; Y7 ^" f6 TLeast significant difference, 最小显著差法9 o& q: N3 I4 D& h$ O- b
Least square method, 最小二乘法
8 x1 B; |9 H2 W- PLeast-absolute-residuals estimates, 最小绝对残差估计
0 F& l) K$ T0 Q. ZLeast-absolute-residuals fit, 最小绝对残差拟合
, F& J. t& A/ OLeast-absolute-residuals line, 最小绝对残差线4 K J' b* @' x9 A
Legend, 图例" S8 {) O2 @& E- Z0 z6 J; L8 ], m
L-estimator, L估计量
- f, V- r* p7 W0 j& QL-estimator of location, 位置L估计量
5 v' ]( m1 H( P4 b8 NL-estimator of scale, 尺度L估计量# t9 H9 |5 q/ y! F8 r# ?
Level, 水平
3 ?; Z: @4 m( DLife expectance, 预期期望寿命
; }: h {' ?$ w6 v) o" l, n/ P' z5 zLife table, 寿命表: }" D" y1 _! N
Life table method, 生命表法$ ~+ L) x- ]- Y
Light-tailed distribution, 轻尾分布. J u) w! K: ~ x' M
Likelihood function, 似然函数, p& T7 {2 ~; ^; S* i) J/ K) T4 [
Likelihood ratio, 似然比5 N U$ Z1 T, s T: b
line graph, 线图
. m) y3 M) L. O- ?Linear correlation, 直线相关
" J7 F% j1 f/ N9 J. e2 oLinear equation, 线性方程
" x0 n4 G6 o8 {3 E4 K3 CLinear programming, 线性规划
, d& g: g9 h2 u% @* OLinear regression, 直线回归# W7 C3 z7 f+ {: b
Linear Regression, 线性回归2 g i& N5 t, ?
Linear trend, 线性趋势6 q# j% n) W3 V0 G" _! w9 ~
Loading, 载荷
z& n/ n' {& Y# i E8 t) SLocation and scale equivariance, 位置尺度同变性
* m6 \8 P) P$ a/ d. E) tLocation equivariance, 位置同变性
( l5 V2 v0 h: a9 |) DLocation invariance, 位置不变性& x4 @* P% }' B) h) B$ G- }( R4 Y
Location scale family, 位置尺度族# B5 G: z( I! w8 @
Log rank test, 时序检验
( x* Z6 i& A/ dLogarithmic curve, 对数曲线# W- z' c6 E, W. y6 d, R
Logarithmic normal distribution, 对数正态分布
) i/ ]. L V1 ^& n) d4 p/ R" T7 ILogarithmic scale, 对数尺度
* M& X' d; m/ n- bLogarithmic transformation, 对数变换
/ ~8 G- a, F; U! R( O) Z7 `$ VLogic check, 逻辑检查
' F$ U( V# a/ b/ @; X) MLogistic distribution, 逻辑斯特分布
+ G. b8 U8 @% ]2 h) VLogit transformation, Logit转换6 O' _- u+ l' ?: g: k# s
LOGLINEAR, 多维列联表通用模型 / a+ z, m Y; ]) ?( x
Lognormal distribution, 对数正态分布
' }7 s( [: O1 T" {" Y: x. @Lost function, 损失函数2 s, _5 H/ ?3 m: @4 i
Low correlation, 低度相关 s3 M6 p2 B. x l" F
Lower limit, 下限
6 f: N+ J8 G4 m) ^Lowest-attained variance, 最小可达方差- l( G. I& `+ d$ S I
LSD, 最小显著差法的简称
`; ]$ t5 q* Q- @$ D2 ]Lurking variable, 潜在变量% Y) a: ]; k' N; b
Main effect, 主效应$ Q5 p Y" {( ~7 S. h# ?( ~* n
Major heading, 主辞标目
: V2 \( U/ k! L' C2 C$ dMarginal density function, 边缘密度函数2 i" B" `1 R) U* i* y; Z
Marginal probability, 边缘概率: z8 Y. _% V& y7 V
Marginal probability distribution, 边缘概率分布
$ f# |# J4 k) R; z5 \' tMatched data, 配对资料# R; E& y3 o6 {) g) n2 {- c! |, O
Matched distribution, 匹配过分布% L8 h3 ^2 k1 c* Z" Q' @
Matching of distribution, 分布的匹配1 }5 f3 l: |; P: b }$ G. T
Matching of transformation, 变换的匹配" _1 s4 G& e; I- i
Mathematical expectation, 数学期望
2 t. A3 Q; E. J) j1 {: N! bMathematical model, 数学模型8 K2 j& e- W, H0 S; q. _1 j! p
Maximum L-estimator, 极大极小L 估计量
1 V; X$ w# I$ N8 LMaximum likelihood method, 最大似然法& A) Y. s ^) e9 M& |( Y
Mean, 均数
1 }: i8 W) u* ^8 aMean squares between groups, 组间均方6 d3 ?6 f l( r# K# D1 \% x
Mean squares within group, 组内均方6 L. |1 X8 G$ t3 ]& I' u
Means (Compare means), 均值-均值比较
+ w( V& C3 J7 r- P' tMedian, 中位数
9 r- x# t; _$ P. L8 zMedian effective dose, 半数效量) V3 E2 c. c1 O) A2 s/ t8 s( C' c; M
Median lethal dose, 半数致死量% w" w: \# ~% ? M- V& u! g
Median polish, 中位数平滑6 P6 C+ J& ^, f
Median test, 中位数检验$ u: \, b/ H! E5 o
Minimal sufficient statistic, 最小充分统计量. b8 h! m0 @9 b U+ z
Minimum distance estimation, 最小距离估计1 z+ x' b0 G/ C' f- i! {
Minimum effective dose, 最小有效量
. |; ~: y4 y( j# P+ OMinimum lethal dose, 最小致死量# Q5 ?7 y' D2 d1 h
Minimum variance estimator, 最小方差估计量
5 Q4 @( D# P2 j' W# @* _MINITAB, 统计软件包
8 C3 n8 f+ o2 p4 rMinor heading, 宾词标目8 |1 V* @6 X R9 [' H K3 |- j, U/ k
Missing data, 缺失值
1 m% x4 J p( q8 |7 aModel specification, 模型的确定( {. K) `# J* a5 K4 m/ A0 p
Modeling Statistics , 模型统计
5 m1 q0 F8 m1 [: J* B r/ cModels for outliers, 离群值模型. t2 t$ b! X. ]' N- ^% ]6 M4 j7 b
Modifying the model, 模型的修正
Y% ^) {( y8 w$ u5 W7 J+ ~0 MModulus of continuity, 连续性模
5 F1 U3 K5 O. wMorbidity, 发病率 6 u& e8 Q3 a1 B# c
Most favorable configuration, 最有利构形4 A, {# W9 g/ K
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
/ R/ P3 {/ Q) E+ J rMultinomial Logistic Regression , 多项逻辑斯蒂回归
1 p8 _! r4 v; g7 ZMultiple comparison, 多重比较* l3 d; u/ n s$ x
Multiple correlation , 复相关0 J9 J% W3 G. J7 C; ^" j5 b) [
Multiple covariance, 多元协方差
0 I) a7 A' P; P. p! D9 eMultiple linear regression, 多元线性回归
- B# }0 |9 x: g; C: O) cMultiple response , 多重选项/ i' D1 R/ v" F5 z* F$ U, ]$ M+ b2 m
Multiple solutions, 多解7 f& c) I3 D" E3 w6 m7 K( D
Multiplication theorem, 乘法定理! [: \6 R) Q ?4 \/ z
Multiresponse, 多元响应
3 w8 Y$ ]& D( B3 P; W/ xMulti-stage sampling, 多阶段抽样7 w9 e5 B$ F) U
Multivariate T distribution, 多元T分布- W' Y, r1 I" @% n* p
Mutual exclusive, 互不相容1 V0 a4 t$ c0 J4 l' ]; ]
Mutual independence, 互相独立
, p5 O9 t5 ^% a; F6 aNatural boundary, 自然边界
( A( Z/ Z3 P9 C- x3 ]7 X* d6 eNatural dead, 自然死亡
! F- a; @* O9 ANatural zero, 自然零
9 ]) `: k1 \" q9 D$ ]# ZNegative correlation, 负相关) ^5 O; P* H# r$ N. q
Negative linear correlation, 负线性相关1 n6 ?7 I" l: j, v# d
Negatively skewed, 负偏5 e1 v4 ?& R$ R$ F J5 e
Newman-Keuls method, q检验5 K' M+ h& {& L% ~9 b' z2 b
NK method, q检验% x3 u& x; _1 n$ ^$ Q
No statistical significance, 无统计意义
7 Y( y- `8 [2 E6 h; INominal variable, 名义变量1 c/ _1 E% ]6 m, i
Nonconstancy of variability, 变异的非定常性
7 j) _' w. m1 E: ~/ VNonlinear regression, 非线性相关
7 @0 h* p/ `1 G4 c( s; JNonparametric statistics, 非参数统计
/ B6 o4 B" J- h3 q' S1 Z* @& BNonparametric test, 非参数检验4 n6 O/ H2 z4 P
Nonparametric tests, 非参数检验2 E, `) d4 e/ L2 y5 |1 M: M7 k
Normal deviate, 正态离差$ x" s* A; G& @% S8 ?
Normal distribution, 正态分布: j8 a( q& X$ H3 q
Normal equation, 正规方程组7 [3 M4 V, s! ~1 y! f8 F3 y) E8 e w2 Q' X
Normal ranges, 正常范围
& O/ _4 z" V, x7 u/ T3 fNormal value, 正常值, }6 I/ a( _0 K9 E+ M% u0 C+ I8 `
Nuisance parameter, 多余参数/讨厌参数
/ c, \+ X! A4 x* |1 {, {( _Null hypothesis, 无效假设 : n0 h1 o! j% v0 E
Numerical variable, 数值变量3 c5 g0 u9 G5 m8 D8 B0 T z
Objective function, 目标函数+ W* n( v, B; i
Observation unit, 观察单位
; S- Y+ _0 i- XObserved value, 观察值! ^9 n/ x' n; J% `* R
One sided test, 单侧检验
& K* J# `: w: E! ^One-way analysis of variance, 单因素方差分析, V3 ~& F! B1 { R2 J- v% |
Oneway ANOVA , 单因素方差分析
9 Y1 q) M5 @! U- COpen sequential trial, 开放型序贯设计/ v& a. g9 G" L! T- o+ ]. h
Optrim, 优切尾
! E+ Z. d3 e- uOptrim efficiency, 优切尾效率
7 Y. ?+ D. j2 qOrder statistics, 顺序统计量8 x) M6 T" @$ N& Z
Ordered categories, 有序分类
0 F, P7 q0 I- Y+ W/ n- GOrdinal logistic regression , 序数逻辑斯蒂回归
# Y$ x7 x& p% X. `4 q0 ?( AOrdinal variable, 有序变量$ V' n% w& P. i6 f* l+ C
Orthogonal basis, 正交基4 ?, T- t3 }# j0 \) p2 \ `
Orthogonal design, 正交试验设计- Z# q7 M% s X9 _
Orthogonality conditions, 正交条件; ?9 P O' ^/ }. T
ORTHOPLAN, 正交设计 , Y ?6 ^8 ~) U0 F5 V/ T% O
Outlier cutoffs, 离群值截断点
1 N1 W! {6 d4 J0 UOutliers, 极端值9 T6 @; H6 R8 P% }4 K) q8 R9 ^
OVERALS , 多组变量的非线性正规相关
; \% \3 T* H7 ]+ T8 d4 G8 NOvershoot, 迭代过度: R6 @" L/ j4 E7 ^" }4 H
Paired design, 配对设计, b3 Q3 `0 C0 _
Paired sample, 配对样本
& y/ X% D R5 n2 k3 bPairwise slopes, 成对斜率2 b/ R0 P, q* k! X
Parabola, 抛物线
* Z P: c; i ^' C5 U8 |+ TParallel tests, 平行试验
4 z+ X* I4 t- D0 o: }" ~Parameter, 参数0 ^2 u. V6 i- _1 J
Parametric statistics, 参数统计. R) D; X H: V# @
Parametric test, 参数检验
$ H- L" n/ s1 n2 i. K) qPartial correlation, 偏相关
1 k. [7 Z* ^- B, Y2 q$ J; ]: D1 EPartial regression, 偏回归
K# b! `* y; Q% h2 Y, |Partial sorting, 偏排序
- M4 n# d# `* j( s. Y1 Q. R: v/ ^Partials residuals, 偏残差- x2 W- z5 b' t6 j' n; \1 z: t; D
Pattern, 模式( \9 |: N2 _6 B0 Y! W, ~
Pearson curves, 皮尔逊曲线
" T) f0 v. f, @3 Z2 X7 t- ]Peeling, 退层( y" u- H' v& O% P; Q3 ?
Percent bar graph, 百分条形图
5 j0 z* e# l! l$ X8 cPercentage, 百分比
! c3 a$ O+ v4 H; i2 K1 w$ [2 e+ X% zPercentile, 百分位数5 M8 d$ }. f6 ]& B1 d! |
Percentile curves, 百分位曲线! m) B9 B P/ I5 Y& O
Periodicity, 周期性0 l ^5 F' |8 d4 b9 q& c. H+ g
Permutation, 排列
4 i0 r+ c! X: Y; qP-estimator, P估计量+ r, u4 c$ J: K# ~' y4 x3 f
Pie graph, 饼图
' _. {/ y6 }" k4 m; r3 nPitman estimator, 皮特曼估计量
5 Z7 T: q: o$ N+ @0 l) V6 ^Pivot, 枢轴量4 Q& ~' r/ m: V. \+ u7 _ K6 g
Planar, 平坦( `2 Q, g8 W& y' @; a) z
Planar assumption, 平面的假设
# d8 ]7 N# k6 D% u- k8 y* |PLANCARDS, 生成试验的计划卡. G7 z h1 r7 L Z7 S6 f! h5 {
Point estimation, 点估计
( Y. C: Z o; Z' } I7 e: lPoisson distribution, 泊松分布
8 X/ _5 @1 o, X" w' SPolishing, 平滑
6 f( T, O/ x7 g+ a1 y( q( Y k) FPolled standard deviation, 合并标准差
" [) q: s- {8 o. k) qPolled variance, 合并方差2 X1 d! l! U) {- @8 S/ {
Polygon, 多边图
. [. W* y0 C. W$ s6 j, g F7 RPolynomial, 多项式" N" R; \; X, q0 N5 I
Polynomial curve, 多项式曲线% t# L/ X3 ~( m3 t5 ?+ x$ s
Population, 总体
0 X5 \/ [7 l7 x0 ]2 t3 \Population attributable risk, 人群归因危险度4 _5 Y" S* R0 c9 d
Positive correlation, 正相关: l5 l* d4 ?. N. F1 c$ ^) h
Positively skewed, 正偏- z4 l3 g5 P. A; F$ a# P0 k
Posterior distribution, 后验分布! D6 z7 A& K, M6 ~/ {
Power of a test, 检验效能
% K3 I8 {& H: K! ]' Z* k4 d) BPrecision, 精密度
7 H- N9 H; I$ uPredicted value, 预测值
' Q7 l- T0 { x6 s& l2 Q# yPreliminary analysis, 预备性分析
' w" d0 z3 _( \1 M4 kPrincipal component analysis, 主成分分析
3 J9 C- k; B$ D6 w( C* y: ?Prior distribution, 先验分布) s' T+ w& I1 t0 a. U, [2 n
Prior probability, 先验概率8 e: s; [* J3 Y1 P+ R3 X
Probabilistic model, 概率模型, A6 y9 e$ D( M& P
probability, 概率( c# l9 ~2 B7 h- Z
Probability density, 概率密度: f' k3 B) A' W
Product moment, 乘积矩/协方差# F* p7 B" b) [8 \: `
Profile trace, 截面迹图# W1 W* y( G! y; j9 F, x$ P
Proportion, 比/构成比
; q" D' P9 w7 y- b: U- pProportion allocation in stratified random sampling, 按比例分层随机抽样4 s* l6 ]8 _' w/ j' v0 o* V
Proportionate, 成比例' ^ s3 G @. v& V% ]- W) z- @9 M9 l
Proportionate sub-class numbers, 成比例次级组含量- b5 a! \+ K2 R7 W2 e( P
Prospective study, 前瞻性调查
" T/ o+ L2 o3 _9 H x6 hProximities, 亲近性
2 ?9 U! j+ [ V) g0 k7 M: OPseudo F test, 近似F检验
, ^6 L: R, u5 N% N9 MPseudo model, 近似模型4 E4 A: H q. t9 }1 z
Pseudosigma, 伪标准差: J+ |: ~; s ]; L: k
Purposive sampling, 有目的抽样* }) {5 A8 X0 R8 |; W
QR decomposition, QR分解: o' r K$ L4 P% f4 B7 j1 Q6 [
Quadratic approximation, 二次近似( e# ]7 H8 ?* |& O
Qualitative classification, 属性分类1 i5 L, @: `5 X: T% x; m8 q5 q
Qualitative method, 定性方法
1 T- X- g! U7 G0 M& b) T U( Y# tQuantile-quantile plot, 分位数-分位数图/Q-Q图
! C! Q( H; K& F( T+ h7 DQuantitative analysis, 定量分析+ F7 ~# i1 F7 K% Q6 ]
Quartile, 四分位数* t* X" R A, O0 g
Quick Cluster, 快速聚类
9 [, a! K( O* m3 HRadix sort, 基数排序
8 p- s" V# J% e3 X ]Random allocation, 随机化分组
! q! t, w- s, I: L+ x. ~7 CRandom blocks design, 随机区组设计$ V1 s. a; B* N( p
Random event, 随机事件# c5 j" J* S. x1 T- E
Randomization, 随机化* \2 }& v3 f( ~( k# s) s' ]
Range, 极差/全距9 G! u- V$ g5 U: W% ?: i. ]; V# R
Rank correlation, 等级相关% U G- o/ d3 h7 H5 ~
Rank sum test, 秩和检验* M7 A1 I& G: K F; r$ F& g# [
Rank test, 秩检验7 Y: K5 e& n% o5 T% o0 j: ~$ O
Ranked data, 等级资料
6 R* Y% [+ v; U/ i0 ^6 aRate, 比率* Z3 m7 g8 \$ t. @6 i
Ratio, 比例
3 X& U, Q; |' b: ~7 PRaw data, 原始资料
3 I. v/ D! P1 H5 s* gRaw residual, 原始残差, |; w* G# P$ ~! h; S( r
Rayleigh's test, 雷氏检验 G; s% M( P6 P; E( ?- P
Rayleigh's Z, 雷氏Z值
, R; ]% b4 Z( H7 X, wReciprocal, 倒数
3 l3 a7 t* X% g; jReciprocal transformation, 倒数变换
$ }) |2 `, O1 VRecording, 记录% N5 E4 J& l) d. @4 c: I F
Redescending estimators, 回降估计量
7 f% _, @! ?! V5 @Reducing dimensions, 降维4 j. G7 Q8 N" v" g$ X, `
Re-expression, 重新表达( W' T1 `' ]. n+ N- g6 A# q
Reference set, 标准组
1 e- {; \! Q& \+ D! e& NRegion of acceptance, 接受域
! ^- t6 q" G! ]% i. r9 |# f% wRegression coefficient, 回归系数5 G. @0 a' \ O
Regression sum of square, 回归平方和4 G- k9 A7 _ s p a! [
Rejection point, 拒绝点
+ A3 q9 M" ]$ ]4 {0 LRelative dispersion, 相对离散度
, D: _1 k6 }& l& @. |( _Relative number, 相对数% R% s5 ?4 O0 `/ ^* G# b0 J9 x; h
Reliability, 可靠性
: O1 s9 J: ^; A# ^5 d" ]Reparametrization, 重新设置参数/ |9 N9 h' N0 u0 h+ P9 E
Replication, 重复! A: G' ]- t$ a9 \8 A X
Report Summaries, 报告摘要3 ]7 t4 y3 ?: p5 ?0 b) `
Residual sum of square, 剩余平方和
2 d+ p* W. ]6 D3 \Resistance, 耐抗性7 U/ @; h. l6 h9 s) H
Resistant line, 耐抗线
9 T* f/ Y$ a# PResistant technique, 耐抗技术
' m2 }: [5 R+ Y$ R% n$ J) bR-estimator of location, 位置R估计量
" E% a3 i) r5 g/ g" X" GR-estimator of scale, 尺度R估计量
( K5 f9 s) s. |Retrospective study, 回顾性调查0 r. [& x4 k7 g/ x7 U4 a% y
Ridge trace, 岭迹/ Y! L3 x& x% \1 c5 \2 {
Ridit analysis, Ridit分析+ S: H/ r4 u" U. r
Rotation, 旋转( v. k- N0 x/ X. i; z
Rounding, 舍入
9 {$ |( N9 J. x- B- u8 Q/ S+ |" DRow, 行
9 S0 C1 K7 R- P) g' yRow effects, 行效应
# c; ^3 c; d# z6 ~1 u1 f) uRow factor, 行因素5 \* p* K' d: n. l' n! C. U, x
RXC table, RXC表4 i& A8 g/ `) A8 c
Sample, 样本 J- o6 [/ {- {' ^
Sample regression coefficient, 样本回归系数 L3 g2 q& n1 ?9 p4 f) @0 t, D4 ~
Sample size, 样本量: O- m2 S( x# c
Sample standard deviation, 样本标准差
2 X* f) J4 m! |! m: [Sampling error, 抽样误差
7 M- Z( @. m0 f% M6 o4 ~# gSAS(Statistical analysis system ), SAS统计软件包7 i4 I' _; x; q8 j# Y
Scale, 尺度/量表: G4 j5 p3 d4 y( T* |0 q& K
Scatter diagram, 散点图
) D! u; h3 r; U- T# hSchematic plot, 示意图/简图. w2 i4 v. a2 M4 |: X7 ]) y
Score test, 计分检验1 B; q$ z$ C7 [
Screening, 筛检- W1 D2 m: b8 u t4 g* {
SEASON, 季节分析 ( u& A& x9 \9 n5 R1 @
Second derivative, 二阶导数
- P( k& W' ]+ e, @- r; PSecond principal component, 第二主成分
: J; v# ~* }( ^" V5 A' lSEM (Structural equation modeling), 结构化方程模型 : d9 p1 N! F5 Y1 D( u, t9 K
Semi-logarithmic graph, 半对数图) D9 j4 }9 B" J1 @
Semi-logarithmic paper, 半对数格纸( P) }6 [2 R) c3 C/ O
Sensitivity curve, 敏感度曲线. E& A' Q( `% ?6 q
Sequential analysis, 贯序分析
B6 V* r" p8 R5 f, hSequential data set, 顺序数据集: p( ^/ n$ O4 F6 q
Sequential design, 贯序设计$ v# N; e! J0 G5 v. Q
Sequential method, 贯序法
$ s' r& y3 Z2 z! w- y+ J1 }& z; V) q& cSequential test, 贯序检验法
. E) p) e) q* G+ X9 ~' n. bSerial tests, 系列试验
4 @0 w/ W2 O' E" sShort-cut method, 简捷法 5 a: u6 ^. R) S- ?' ^
Sigmoid curve, S形曲线
) k& t0 {8 s% X0 JSign function, 正负号函数
3 r8 z% z! \# E% M( e% n+ [9 O1 [Sign test, 符号检验6 S' O* t) P+ B: ]6 U/ C" D( R
Signed rank, 符号秩
; _& ?0 u, F" f; p: mSignificance test, 显著性检验- }+ a$ o0 _* W$ L' f
Significant figure, 有效数字
/ ~* y6 C4 `; l, PSimple cluster sampling, 简单整群抽样; M$ m( B) Y* [, U3 k/ Y
Simple correlation, 简单相关1 o# u8 g6 e4 x7 O' l
Simple random sampling, 简单随机抽样
. @& O" o# T3 f/ `) e* nSimple regression, 简单回归0 L( p; @2 @- H
simple table, 简单表
. p6 F2 A2 z! H; u0 @! a! ^& HSine estimator, 正弦估计量5 A: m) y* f y% J) N6 a
Single-valued estimate, 单值估计
% U! \4 |1 D5 `5 G8 L" ASingular matrix, 奇异矩阵 b$ b6 e: d" I/ o+ O
Skewed distribution, 偏斜分布
' f5 @4 o; H NSkewness, 偏度7 E- S3 S5 X* K: Y; f b; n
Slash distribution, 斜线分布
7 \- l: u; N( T3 S! C+ uSlope, 斜率; y. `* d& j, j$ U. V4 V
Smirnov test, 斯米尔诺夫检验
$ h- U L/ [& K; `6 H3 ISource of variation, 变异来源
& k [ I. T$ o3 gSpearman rank correlation, 斯皮尔曼等级相关
) f! `" P8 N5 A1 NSpecific factor, 特殊因子) y j# N# A* ?3 j. V
Specific factor variance, 特殊因子方差, `) I& Y3 e, I
Spectra , 频谱
* E& G4 {5 ?, e/ ?; x2 ASpherical distribution, 球型正态分布& n4 X5 v4 `, C7 Q/ _
Spread, 展布7 r0 w1 \) M0 a/ i* o, m9 R7 f
SPSS(Statistical package for the social science), SPSS统计软件包' a* J$ k- Z; L( x& ]$ j' O
Spurious correlation, 假性相关; R3 u" l% \. C' x
Square root transformation, 平方根变换: y& x9 H) h8 i7 Y% l4 g& s
Stabilizing variance, 稳定方差5 t( U+ L4 D7 E8 T6 |. r7 c
Standard deviation, 标准差
# k1 u4 w: m0 }6 n7 j1 \/ GStandard error, 标准误2 W+ i* q# z+ d* q$ z
Standard error of difference, 差别的标准误8 t f; |# r6 N% [( i6 _4 v9 P
Standard error of estimate, 标准估计误差7 e4 s4 }+ g \+ y
Standard error of rate, 率的标准误
! u- i q+ B: xStandard normal distribution, 标准正态分布! e% D( x( Z/ q6 f2 b
Standardization, 标准化- i( ]6 Z; T- I: T7 B) n0 {
Starting value, 起始值7 F, t3 F E1 s3 R3 X1 S) r9 K# b
Statistic, 统计量& b' D( |3 n( g: @; j( A
Statistical control, 统计控制
4 H9 [: O% s/ P# N1 i& mStatistical graph, 统计图
5 L" ~2 l' e+ z& TStatistical inference, 统计推断0 A7 d8 @* I6 f: t" N# i
Statistical table, 统计表: s- [% m4 _: U% Q7 i9 f. `
Steepest descent, 最速下降法
. o8 V% {0 \3 v6 U. w* _Stem and leaf display, 茎叶图$ z6 J5 p$ [- V" {: d. U; x
Step factor, 步长因子
. G. ^! o1 N# C( j \; P9 GStepwise regression, 逐步回归" C" E# z# J, `1 ^# H
Storage, 存. I I! u$ _6 M" M/ Q
Strata, 层（复数）
+ B" _7 b" o2 C8 v9 MStratified sampling, 分层抽样
+ |! }' Y, |$ N4 W& @: QStratified sampling, 分层抽样
" g: Y8 |% A- f- Y' QStrength, 强度9 t* w7 m; j1 _) j/ ?, _
Stringency, 严密性
4 m3 H1 X! E! S' P. q* ?Structural relationship, 结构关系
3 C! a, y7 q* R) [( n" r8 TStudentized residual, 学生化残差/t化残差
4 Q& u5 k2 {8 X, DSub-class numbers, 次级组含量
( ?$ u" T# g+ f6 N, @& g5 ^Subdividing, 分割 S: G4 H: m& j$ c8 R
Sufficient statistic, 充分统计量
- Z7 l4 u2 t5 `8 iSum of products, 积和
- y. Y& i8 e* ] ^) nSum of squares, 离差平方和
% }1 {! E* _1 {" C$ o/ bSum of squares about regression, 回归平方和
" n* t) s J% R, E/ e1 v- zSum of squares between groups, 组间平方和
& U1 P5 o( K" dSum of squares of partial regression, 偏回归平方和
0 \- s7 h, a" y. vSure event, 必然事件1 T" J9 R3 ]3 F: F, t- [
Survey, 调查$ E+ X, H2 C4 a, [3 d
Survival, 生存分析 @0 V4 a- F/ x2 ?# e9 y5 d
Survival rate, 生存率
. n$ E' U! L; D1 a4 v: t% y5 BSuspended root gram, 悬吊根图$ u. M( p* [* v. a
Symmetry, 对称3 T: q3 F# t$ ~% A- j; ^
Systematic error, 系统误差
* W5 ^5 U; f* I" t, M+ i [0 ?Systematic sampling, 系统抽样
) \9 k2 l) r+ z3 r) zTags, 标签
4 F7 U+ Y. j( I* u$ fTail area, 尾部面积
! a2 _% z- ~0 z+ b, qTail length, 尾长. ^9 g+ Z! h! u3 ?
Tail weight, 尾重) d4 p/ q1 u* ^2 J* G
Tangent line, 切线
/ b ?: | G" }3 h0 R& U8 HTarget distribution, 目标分布! `0 l" v( J! e1 H% d
Taylor series, 泰勒级数
( e2 H- n2 c% W" p1 H4 F5 QTendency of dispersion, 离散趋势% t& r5 V8 c' v5 Q5 Q! H
Testing of hypotheses, 假设检验
4 @- h# C- i% q8 }; ]/ F$ pTheoretical frequency, 理论频数3 {; r; C8 s5 c( ~( p; k
Time series, 时间序列
9 H+ y, K$ e( w3 kTolerance interval, 容忍区间8 x4 B6 p: H1 _
Tolerance lower limit, 容忍下限
\/ l' v3 C. fTolerance upper limit, 容忍上限
' R C% D! ~0 K0 M$ ?! [ GTorsion, 扰率& C( o( a+ U2 u
Total sum of square, 总平方和
- E. Z0 Y% `9 W BTotal variation, 总变异+ B8 d+ q) v" b3 H1 W0 M x2 q
Transformation, 转换
' ]$ |3 c( I `8 eTreatment, 处理$ f& a/ {+ h7 U2 Q3 b
Trend, 趋势6 h. }% i* h7 m+ b. `2 k% U! i
Trend of percentage, 百分比趋势
" E& G$ x1 x6 ^! HTrial, 试验
1 R, ]2 T0 ^% P( ^( aTrial and error method, 试错法
9 K3 G2 U: H8 h; f% kTuning constant, 细调常数4 p! Y% `: \( \- j- W1 r
Two sided test, 双向检验6 v! w8 e, b7 |* I6 t* p# P& |. \& h
Two-stage least squares, 二阶最小平方5 `% z2 ?8 H/ T0 X1 r; E5 Y$ j8 q
Two-stage sampling, 二阶段抽样8 \ ]; N- c* z4 M3 ^, E! D- c
Two-tailed test, 双侧检验% s1 J9 Y9 n* ^! S
Two-way analysis of variance, 双因素方差分析
7 g% R% B8 H' l+ V H) D$ n5 JTwo-way table, 双向表
1 @8 g6 ?+ L+ m A8 p/ o" TType I error, 一类错误/α错误+ \$ \; e% N& X9 [* g6 Z
Type II error, 二类错误/β错误
8 H* n! R, q# ^- K$ pUMVU, 方差一致最小无偏估计简称- ^! G2 u( u) D) k
Unbiased estimate, 无偏估计* E- \' B# W+ `* d& @
Unconstrained nonlinear regression , 无约束非线性回归
* @3 j& j" G2 }, LUnequal subclass number, 不等次级组含量
, J2 X$ x! {( sUngrouped data, 不分组资料3 t7 o5 v2 K( _6 w) I! D
Uniform coordinate, 均匀坐标
7 r" L/ X( \# L9 }Uniform distribution, 均匀分布" r9 W6 l. Q: c% Z
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
1 x+ P/ P9 A) v" LUnit, 单元
% f4 d W! `. r; NUnordered categories, 无序分类4 X a7 B6 _( `6 R0 v- f3 S
Upper limit, 上限2 @2 z8 M! e/ Q w; x4 T
Upward rank, 升秩8 [9 B! j; ^' E$ C
Vague concept, 模糊概念
+ v/ u* w$ g o/ y* W, a. q5 ?Validity, 有效性
8 q" n# L% I5 {2 G/ L1 zVARCOMP (Variance component estimation), 方差元素估计
1 m( D8 [, H" X0 q/ fVariability, 变异性
; {% E, r t( c& D+ Q8 V/ ~& l" OVariable, 变量/ {% c* A O8 g' f1 V
Variance, 方差
5 y3 U5 ~+ B# Q& RVariation, 变异" P0 r2 ]9 b3 t/ h. C1 Z
Varimax orthogonal rotation, 方差最大正交旋转
% ?" d3 S: \( Z0 |2 [Volume of distribution, 容积
$ ~1 M1 F, w. L8 z7 SW test, W检验
$ ~! Z9 A, j3 y9 o) f$ HWeibull distribution, 威布尔分布2 q |* t U2 D
Weight, 权数
4 ~ }2 B2 |" l- p- h: [$ z! CWeighted Chi-square test, 加权卡方检验/Cochran检验( v1 N$ p# P W W
Weighted linear regression method, 加权直线回归0 U O0 V6 |* E% R
Weighted mean, 加权平均数
3 I" Z+ |% M6 `( f7 R* w1 H0 o" m4 wWeighted mean square, 加权平均方差
6 |; j9 A% @' ~9 L, ^# {, XWeighted sum of square, 加权平方和
! \1 y; F0 ?; c/ b+ RWeighting coefficient, 权重系数
7 V8 u4 c; C3 {, S2 y5 P6 kWeighting method, 加权法 & S' g3 J& u* _: v! b2 @7 j5 w
W-estimation, W估计量( S% h4 M) R" J4 Y, a; _4 h0 G
W-estimation of location, 位置W估计量' l0 Q8 C* m: N8 f- U3 c( N8 y5 v
Width, 宽度+ k0 |5 {: u2 \. d
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验/ ]: a3 t. q4 g4 j4 o/ j
Wild point, 野点/狂点3 G2 r$ ^( ?& t# ^" r" r' K( J
Wild value, 野值/狂值
" C- Q8 C% y3 }Winsorized mean, 缩尾均值. u, n, j, e. l ^7 l8 f- }+ S6 d
Withdraw, 失访 6 ^4 k6 U: @. J* z" V$ O
Youden's index, 尤登指数
% ^5 U1 K9 T6 W, I5 g& y# GZ test, Z检验
' _3 ~2 f6 H( a2 BZero correlation, 零相关
/ y7 h+ @' ?& j8 R& T0 @Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
